Nicolas L. Dzamko

Machine learning-based image analysis of Parkinson's disease iPS-derived neurons predicts genotype and reveals mitochondria-lysosome abnormalities

The paper uses machine learning to analyze neuronal morphology in Parkinson's disease iPSC-derived neurons, identifying genotype-specific mitochondrial and lysosomal abnormalities.

Dopamine and cortical iPSC-derived neurons with different Parkinsonian mutations show variation in lysosomal and mitochondrial dysfunction: implications for protein deposition versus selective cell loss

This study compares dopamine and cortical neurons with PD mutations to identify cellular dysfunctions linked to different pathological phenotypes.

Novel tools to quantify total, phospho-Ser129 and aggregated alpha-synuclein in the mouse brain

The paper develops and validates new immunoassays for quantifying total, phospho-Ser129, and aggregated alpha-synuclein in mouse brain tissue.

Single molecule fingerprinting reveals different growth mechanisms in seed amplification assays for different polymorphs of alpha Synuclein fibrils.

The paper uses single molecule techniques to show that different alpha-synuclein polymorphs have distinct growth mechanisms in seed amplification assays, with one polymorph showing increased secondary nucleation.

A potential patient stratification biomarker for Parkinson's disease based on LRRK2 kinase-mediated centrosomal alterations in peripheral blood-derived cells

Peripheral blood-derived cells can be employed to stratify Parkinson's disease patients most likely to respond to LRRK2-related therapeutics.